Monise Terra Cerezini

Exerccios da Aula 8 - Regresso Mltipla

#Galileu estava Certo?

init.h = c(600, 700, 800, 950, 1100, 1300, 1500) 
h.d = c(253, 337, 395, 451, 495, 534, 573) 

plot(h.d~init.h) 

mod1 <- lm(h.d~init.h) 

mod2 <- lm(h.d~init.h+I(init.h^2)) 

anova(mod1,mod2) 

abline(mod1) 
cf.m2 <- coef(mod2) 
curve(cf.m2[1]+cf.m2[2]*x+cf.m2[3]*x^2, add=T, lty=2) 

summary(mod2) 

mod3 <- lm(h.d~init.h+I(init.h^2)+I(init.h^3)) 
cf.m3 <- coef(mod3) 
curve(cf.m3[1]+cf.m3[2]*x+cf.m3[3]*x^2+cf.m3[4]*x^3, add=T, lty=10,col="blue")

R= O polinmio de terceiro grau  um melhor modelo para descrever os dados do experimento de Galileu, pois o valor de 
p  altamente significativo.

 

#Massa de Recm-Nascidos

babies <- read.table(file='babies.txt',header=T) 
str(babies) 
head(babies)

*Eliminnando as observaes com dados faltantes 

babies[which(babies$bwt==999),] 
babies[which(babies$gestation==999),] 

babies$gestation[which(babies$gestation==999)]<- NA 

babies[which(babies$parity==9),] 
babies[which(babies$height==99),] 

babies$height[which(babies$height==99)]<- NA 

babies[which(babies$weight==999),] 

babies$weight[which(babies$weight==999)]<- NA 

babies[which(babies$smoke==9),] 

babies$smoke[which(babies$smoke==9)]<- NA 

babies$smoke<- factor(babies$smoke) 
babies$parity<- factor(babies$parity) 

*Anova

anova(lm(bwt~gestation, data=babies)) 
anova(lm(bwt~parity, data=babies)) 
anova(lm(bwt~age, data=babies)) 
anova(lm(bwt~height, data=babies)) 
anova(lm(bwt~weight, data=babies)) 
anova(lm(bwt~smoke, data=babies)) 



m.final<-lm(babies$bwt~babies$gestation+babies$height+babies$smoke,data=babies) 
anova(m.final) 
summary(m.final) 

R= As variveis que mais influenciam a variao encontrada na massa dos bebes ao nascer so: gestation, height e smoke.

